A tiny (305B) browser utility for stringifying a query Object.
You should only consider using this within a browser context since Node's built-in querystring.stringify
is much faster and should be used in a Node environment! An ideal use case is serializing a query object before an API request is sent.
This module exposes three module definitions:
- ES Module:
dist/qss.mjs
- CommonJS:
dist/qss.js
- UMD:
dist/qss.min.js
$ npm install --save qss
import { encode, decode } from 'qss';
encode({ foo:'hello', bar:[1,2,3], baz:true });
//=> 'foo=hello&bar=1&bar=2&bar=3&baz=true'
encode({ foo:123 }, '?');
//=> '?foo=123'
encode({ bar:'world' }, 'foo=hello&');
//=> 'foo=hello&bar=world'
decode('foo=hello&bar=1&bar=2&bar=3&baz=true');
//=> { foo:'hello', bar:[1,2,3], baz:true };
Returns: String
Returns the formatted querystring.
Type: Object
The object that contains all query parameter keys & their values.
Type: String
Default: ''
An optional prefix. The stringified params
will be appended to this value, so it must end with your desired joiner; eg ?
.
Important: No checks or validations will run on your
prefix
. Similarly, no character is used to "glue" the query string to yourprefix
string.
Returns: Object
Returns an Object with decoded keys and values.
Repetitive keys will form an Array of its values. Also, qss
will attempt to typecast Boolean
and Number
values.
Type: String
The query string, with or without its leading ?
character.
qss.decode(
location.search.substring(1) // removes the "?"
);
Running Node v14.5.0
Encode
qss x 1,151,789 ops/sec ±0.66% (89 runs sampled)
native x 4,432,282 ops/sec ±1.47% (90 runs sampled)
querystringify x 644,980 ops/sec ±0.70% (93 runs sampled)
query-string x 209,326 ops/sec ±0.63% (94 runs sampled)
qs x 514,285 ops/sec ±0.68% (89 runs sampled)
Decode
qss x 504,873 ops/sec ±3.95% (87 runs sampled)
native x 1,148,267 ops/sec ±0.68% (94 runs sampled)
querystringify x 193,010 ops/sec ±0.94% (91 runs sampled)
query-string x 138,808 ops/sec ±1.15% (90 runs sampled)
qs x 137,275 ops/sec ±0.77% (94 runs sampled)
MIT © Luke Edwards